An integrated in vitro carcinogenicity test that distinguishes between genotoxic carcinogens, non-genotoxic carcinogens, and non-carcinogens.

Chemical safety testing plays a crucial role in product and pharmacological development, as well as chemoprevention; however, in vitro genotoxicity safety tests do not always accurately predict the chemicals that will be in vivo carcinogens. If chemicals test positive in vitro for genotoxicity but negative in vivo, this can contribute to unnecessary testing in animals used to confirm erroneous in vitro positive results. Current in vitro tests typically evaluate only genotoxicity endpoints, which limits their potential to detect non-genotoxic carcinogens. The frequency of misleading in vitro positive results can be high, leading to a requirement for more informative in vitro tests. It is now recognized that multiple-endpoint genotoxicity testing may aid more accurate detection of carcinogens and non-carcinogens. The objective of this review was to evaluate the utility of our novel, multiple-endpoint in vitro test, which uses multiple cancer-relevant endpoints to predict carcinogenic potential. The tool assessed micronucleus frequency, p53 expression, p21 expression, mitochondrial respiration, cell cycle abnormalities and, uniquely, cell morphology changes in human lymphoblastoid cell lines, TK6 and MCL-5. The endpoints were used to observe cellular responses to 18 chemicals within the following categories: genotoxic carcinogens, non-genotoxic carcinogens, toxic non-carcinogens, and misleading in vitro positive and negative agents. The number of endpoints significantly altered for each chemical was considered, alongside the holistic Integrated Signature of Carcinogenicity score, derived from the sum of fold changes for all endpoints. Following the calculation of an overall score from these measures, carcinogens exhibited greater potency than non-carcinogens. Genotoxic carcinogens were generally more potent than non-genotoxic carcinogens. This novel approach therefore demonstrated potential for correctly predicting whether chemicals with unknown mechanism may be considered carcinogens. Overall, while further validation is recommended, the test demonstrates potential for the identification of carcinogenic compounds. Adoption of the approach could enable reduced animal use in carcinogenicity testing.

A multi-biomarker micronucleus assay using imaging flow cytometry.

Genetic toxicity testing assesses the potential of compounds to cause DNA damage. There are many genetic toxicology screening assays designed to assess the DNA damaging potential of chemicals in early drug development aiding the identification of promising drugs that have low-risk potential for causing genetic damage contributing to cancer risk in humans. Despite this, in vitro tests generate a high number of misleading positives, the consequences of which can lead to unnecessary animal testing and/or the abandonment of promising drug candidates. Understanding chemical Mode of Action (MoA) is vital to identifying the true genotoxic potential of substances and, therefore, the risk translation into the clinic. Here we demonstrate a simple, robust protocol for staining fixed, human-lymphoblast p53 proficient TK6 cells with antibodies against É£H2AX, p53 and pH3S28 along with DRAQ5™ DNA staining that enables analysis of un-lysed cells via microscopy approaches such as imaging flow cytometry. Here, we used the Cytek® Amnis® ImageStream®X Mk II which provides a high-throughput acquisition platform with the sensitivity of flow cytometry and spatial morphological information associated with microscopy. Using the ImageStream manufacturer's software (IDEAS® 6.2), a masking strategy was developed to automatically detect and quantify micronucleus events (MN) and characterise biomarker populations. The gating strategy developed enables the generation of a template capable of automatically batch processing data files quantifying cell-cycle, MN, É£H2AX, p53 and pH3 populations simultaneously. In this way, we demonstrate how a multiplex system enables DNA damage assessment alongside MN identification using un-lysed cells on the imaging flow cytometry platform. As a proof-of-concept, we use the tool chemicals carbendazim and methyl methanesulphonate (MMS) to demonstrate the assay's ability to correctly identify clastogenic or aneugenic MoAs using the biomarker profiles established.

Nitrosamine acceptable intakes should consider variation in molecular weight: The implication of stoichiometric DNA damage.

N-nitrosamines (NAs) are a class of compounds of which many, especially of the small dialkyl type, are indirect acting DNA alkylating mutagens. Their presence in pharmaceuticals is subject to very strict acceptable daily intake (AI) limits, which are traditionally expressed on a mass basis. Here we demonstrate that AIs that are not experimentally derived for a specific compound, but via statistical extrapolation or read across to a suitable analog, should be expressed on a molar scale or corrected for the target substance's molecular weight. This would account for the mechanistic aspect that each nitroso group can, at maximum, account for a single DNA mutation and the number of molecules per mass unit is proportional to the molecular weight (MW). In this regard we have re-calculated the EMA 18 ng/day regulatory default AI for unknown nitrosamines on a molar scale and propose a revised default AI of 163 pmol/day. In addition, we provide MW-corrected AIs for those nitrosamine drug substance related impurities (NDSRIs) for which EMA has pre-assigned AIs by read-across. Regulatory acceptance of this fundamental scientific tenet would allow one to derive nitrosamine limits for NDSRIs that both meet the health-protection goals and are technically feasible.

Empirical comparison of genotoxic potency estimations: the in vitro DNA-damage ToxTracker endpoints versus the in vivo micronucleus assay.

Genetic toxicology is an essential component of compound safety assessment. In the face of a barrage of new compounds, higher throughput, less ethically divisive in vitro approaches capable of effective, human-relevant hazard identification and prioritisation are increasingly important. One such approach is the ToxTracker assay, which utilises murine stem cell lines equipped with green fluorescent protein (GFP)-reporter gene constructs that each inform on distinct aspects of cellular perturbation. Encouragingly, ToxTracker has shown improved sensitivity and specificity for the detection of known in vivo genotoxicants when compared to existing 'standard battery' in vitro tests. At the current time however, quantitative genotoxic potency correlations between ToxTracker and well-recognised in vivo tests are not yet available. Here we use dose-response data from the three DNA-damage-focused ToxTracker endpoints and from the in vivo micronucleus assay to carry out quantitative, genotoxic potency estimations for a range of aromatic amine and alkylating agents using the benchmark dose (BMD) approach. This strategy, using both the exponential and the Hill BMD model families, was found to produce robust, visually intuitive and similarly ordered genotoxic potency rankings for 17 compounds across the BSCL2-GFP, RTKN-GFP and BTG2-GFP ToxTracker endpoints. Eleven compounds were similarly assessed using data from the in vivo micronucleus assay. Cross-systems genotoxic potency correlations for the eight matched compounds demonstrated in vitro-in vivo correlation, albeit with marked scatter across compounds. No evidence for distinct differences in the sensitivity of the three ToxTracker endpoints was found. The presented analyses show that quantitative potency determinations from in vitro data enable more than just qualitative screening and hazard identification in genetic toxicology.

Multiple-endpoint in vitro carcinogenicity test in human cell line TK6 distinguishes carcinogens from non-carcinogens and highlights mechanisms of action.

Current in vitro genotoxicity tests can produce misleading positive results, indicating an inability to effectively predict a compound's subsequent carcinogenic potential in vivo. Such oversensitivity can incur unnecessary in vivo tests to further investigate positive in vitro results, supporting the need to improve in vitro tests to better inform risk assessment. It is increasingly acknowledged that more informative in vitro tests using multiple endpoints may support the correct identification of carcinogenic potential. The present study, therefore, employed a holistic, multiple-endpoint approach using low doses of selected carcinogens and non-carcinogens (0.001-770 µM) to assess whether these chemicals caused perturbations in molecular and cellular endpoints relating to the Hallmarks of Cancer. Endpoints included micronucleus induction, alterations in gene expression, cell cycle dynamics, cell morphology and bioenergetics in the human lymphoblastoid cell line TK6. Carcinogens ochratoxin A and oestradiol produced greater Integrated Signature of Carcinogenicity scores for the combined endpoints than the "misleading" in vitro positive compounds, quercetin, 2,4-dichlorophenol and quinacrine dihydrochloride and toxic non-carcinogens, caffeine, cycloheximide and phenformin HCl. This study provides compelling evidence that carcinogens can successfully be distinguished from non-carcinogens using a holistic in vitro test system. Avoidance of misleading in vitro outcomes could lead to the reduction and replacement of animals in carcinogenicity testing.

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25-5.0 µg/mL) and/or carbendazim (0.8-1.6 µg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the "DeepFlow" neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for 'mononucleates', 'binucleates', 'mononucleates with MN' and 'binucleates with MN', respectively. Successful classifications of 'trinucleates' (90%) and 'tetranucleates' (88%) in addition to 'other or unscorable' phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.

A weight of evidence assessment of the genotoxicity of 2,6-xylidine based on existing and new data, with relevance to safety of lidocaine exposure.

Lidocaine has not been associated with cancer in humans despite 8 decades of therapeutic use. Its metabolite, 2,6-xylidine, is a rat carcinogen, believed to induce genotoxicity via N-hydroxylation and DNA adduct formation, a non-threshold mechanism of action. To better understand this dichotomy, we review literature pertaining to metabolic activation and genotoxicity of 2,6-xylidine, identifying that it appears resistant to N-hydroxylation and instead metabolises almost exclusively to DMAP (an aminophenol). At high exposures (sufficient to saturate phase 2 metabolism), this may undergo metabolic threshold-dependent activation to a quinone-imine with potential to redox cycle producing ROS, inducing cytotoxicity and genotoxicity. A new rat study found no evidence of genotoxicity in vivo based on micronuclei in bone marrow, comets in nasal tissue or female liver, despite high level exposure to 2,6-xylidine (including metabolites). In male liver, weak dose-related comet increases, within the historical control range, were associated with metabolic overload and acute systemic toxicity. Benchmark dose analysis confirmed a non-linear dose response. The weight of evidence indicates 2,6-xylidine is a non-direct acting (metabolic threshold-dependent) genotoxin, and is not genotoxic in vivo in rats in the absence of acute systemic toxic effects, which occur at levels 35 × beyond lidocaine-related exposure in humans.

Detection of urethane-induced genotoxicity in vitro using metabolically competent human 2D and 3D spheroid culture models.

In vitro genotoxicity studies are a quick and high throughput approach to assess the genotoxic potential of chemicals; however, the reliability of these tests and their relevance to in vivo effects depends on the choice of representative cell line and optimisation of assay conditions. For chemicals like urethane that require specific metabolic activation to cause genotoxicity, it is important that in vitro tests are conducted using cell lines exhibiting the activity and induction of CYP450 enzymes, including CYP2E1 enzyme that is important in the metabolism of urethane, at a concentration representing actual or perceived chemical exposure. We compared 2D MCL-5 cells and HepG2 cells with 3D HepG2 hanging drop spheroids to determine the genotoxicity of urethane using the micronucleus assay. Our 2D studies with MCL-5 did not show any statistically significant genotoxicity [99% relative population doubling (RPD)] compared to controls for concentrations and time point tested in vitro. HepG2 cells grown as 2D indicated that exposure to urethane of up to 30 mM for 23 h did not cause any genotoxic effect (102% RPD) but, at higher concentrations, genotoxicity was produced with only 89-85% RPD. Furthermore, an exposure of 20-50 mM for 23 h using 3D hanging drop spheroid assays revealed a higher MN frequency, thus exhibiting in vitro genotoxicity of urethane in metabolically active cell models. In comparison with previous studies, this study indicated that urethane genotoxicity is dose, sensitivity of cell model (2D vs. 3D) and exposure dependent.

Correction to: Re: Gi et al. 2018, In vivo positive mutagenicity of 1,4-dioxane and quantitative analysis of its mutagenicity and carcinogenicity in rats, Archives of Toxicology 92:3207-3221.

The publisher would like to apologize for the failed cross-linking to the following Letter to the Editor by Paul A.

Investigating FlowSight® imaging flow cytometry as a platform to assess chemically induced micronuclei using human lymphoblastoid cells in vitro.

Use of imaging flow cytometry to assess induced DNA damage via the cytokinesis block micronucleus (CBMN) assay has thus far been limited to radiation dosimetry in human lymphocytes using high end, 'ImageStream X' series imaging cytometers. Its potential to enumerate chemically induced DNA damage using in vitro cell lines remains unexplored. In the present manuscript, we investigate the more affordable FlowSight® imaging cytometry platform to assess in vitro micronucleus (MN) induction in the human lymphoblastoid TK6 and metabolically competent MCL-5 cells treated with Methyl Methane Sulfonate (MMS) (0-5 µg/ml), Carbendazim (0-1.6 µg/ml), and Benzo[a]Pyrene (B[a]P) (0-6.3 µg/ml) for a period of 1.5-2 cell-cycles. Cells were fixed, and nuclei and MN were stained using the fluorescent nuclear dye DRAQ5™. Image acquisition was carried out using a 20X objective on a FlowSight® imaging cytometer (Amnis, part of Merck Millipore) equipped with a 488 nm laser. Populations of ∼20000 brightfield cell images, alongside DRAQ5™ stained nuclei/MN were rapidly collected (≤10 min). Single, in-focus cells suitable for scoring were then isolated using the IDEAS® software. An overlay of the brightfield cell outlines and the DRAQ5 nuclear fluorescence was used to facilitate scoring of mono-, bi-, tri-, and tetra-nucleated cells with or without MN events and in context of the cytoplasmic boundary of the parent cell.To establish the potential of the FlowSight® platform, and to establish 'ground truth' cell classification for the supervised machine learning based scoring algorithm that represents the next stage of our project, the captured images were scored manually. Alongside, MN frequencies were also derived using the 'gold standard' light microscopy and manual scoring. A minimum of 3000 bi-nucleated cells were assessed using both approaches. Using the benchmark dose approach, the comparability of genotoxic potency estimations for the different compounds and cell lines was assessed across the two scoring platforms as highly similar. This study therefore provides essential proof-of-concept that FlowSight® imaging cytometry is capable of reproducing the results of 'gold standard' manual scoring by light microscopy. We conclude that, with the right automated scoring algorithm, imaging flow cytometry could revolutionise the reportability and scoring throughput of the CBMN assay.

A novel, integrated in vitro carcinogenicity test to identify genotoxic and non-genotoxic carcinogens using human lymphoblastoid cells.

Human exposure to carcinogens occurs via a plethora of environmental sources, with 70-90% of cancers caused by extrinsic factors. Aberrant phenotypes induced by such carcinogenic agents may provide universal biomarkers for cancer causation. Both current in vitro genotoxicity tests and the animal-testing paradigm in human cancer risk assessment fail to accurately represent and predict whether a chemical causes human carcinogenesis. The study aimed to establish whether the integrated analysis of multiple cellular endpoints related to the Hallmarks of Cancer could advance in vitro carcinogenicity assessment. Human lymphoblastoid cells (TK6, MCL-5) were treated for either 4 or 23 h with 8 known in vivo carcinogens, with doses up to 50% Relative Population Doubling (maximum 66.6 mM). The adverse effects of carcinogens on wide-ranging aspects of cellular health were quantified using several approaches; these included chromosome damage, cell signalling, cell morphology, cell-cycle dynamics and bioenergetic perturbations. Cell morphology and gene expression alterations proved particularly sensitive for environmental carcinogen identification. Composite scores for the carcinogens' adverse effects revealed that this approach could identify both DNA-reactive and non-DNA reactive carcinogens in vitro. The richer datasets generated proved that the holistic evaluation of integrated phenotypic alterations is valuable for effective in vitro risk assessment, while also supporting animal test replacement. Crucially, the study offers valuable insights into the mechanisms of human carcinogenesis resulting from exposure to chemicals that humans are likely to encounter in their environment. Such an understanding of cancer induction via environmental agents is essential for cancer prevention.

The impact of rural outreach programs on medical students' future rural intentions and working locations: a systematic review.

BACKGROUND: Significant investment has been undertaken by many countries into 'Rural Clinical Training Placement Schemes' for medical students in order to deal with shortages of trained health care professionals in rural and remote locations. This systematic review examines the evidence base of rural educational programs within medical education and focusses on workforce intentions and employment outcomes. The study provides a detailed description of the methodological characteristics of the literature, thematic workforce outcomes and key related factors are identified, study quality is assessed, and the findings are compared within an international context. METHODS: A systematic review looking at international literature of rural placement programs within medical education between January 2005 to January 2017 from databases including; Medline, Embase, NursingOVID, PubMed and Cochrane. The study adopted the PRISMA protocol. A quality assessment of the literature was conducted based on the Health Gains Notation Framework. RESULTS: Sixty two papers met the inclusion criteria. The review identified three program classifications; Rural Clinical Placement Programs, Rural Clinical Placement Programs combined with a rural health educational curriculum component and Rural Clinical School Programs. The studies included were from Australia, United States, Canada, New Zealand, Thailand and Africa. Questionnaires and tracking or medical registry databases were the most commonly reported research tools and the majority were volunteer programs. Most studies identified potential rural predictors/confounders, however a number did not apply control groups and most programs were based on a single site. There was a clear discrepancy in the ideal rural clinical placement length. Outcomes themes were identified related to rural workforce outcomes. Most studies reported that an organised, well-funded, rural placement or rural clinical school program produced positive associations with increased rural intentions and actual graduate rural employment. CONCLUSIONS: Future research should focus on large scale methodologically rigorous multi-site rural program studies, with longitudinal follow up of graduates working locations. Studies should apply pre-and post-intervention surveys to measure change in attitudes and control for predictive confounders, control groups should be applied; and in-depth qualitative research should be considered to explore the specific factors of programs that are associated with encouraging rural employment.

Development of an in vitro PIG-A gene mutation assay in human cells.

Mutagens can be carcinogens, and traditionally, they have been identified in vitro using the Salmonella 'Ames' reverse mutation assay. However, prokaryotic DNA packaging, replication and repair systems are mechanistically very different to those in the humans we inevitably seek to protect. Therefore, for many years, mammalian cell line genotoxicity assays that can detect eukaryotic mutagens as well as clastogens and aneugens have been used. The apparent lack of specificity in these largely rodent systems, due partly to their mutant p53 status, has contributed to the use of animal studies to resolve data conflicts. Recently, silencing mutations at the PIG-A locus have been demonstrated to prevent glycophosphatidylinositol (GPI) anchor synthesis and consequentially result in loss of GPI-anchored proteins from the cell's extracellular surface. The successful exploitation of this mutant phenotype in animal studies has triggered interest in the development of an analogous in vitro PIG-A mutation screening assay. This article describes the development of a robust assay design using metabolically active human cells. The assay includes viability and cell membrane integrity assessment and conforms to the future ideas of the 21st-century toxicology testing.

Evaluation of the automated MicroFlow® and Metafer™ platforms for high-throughput micronucleus scoring and dose response analysis in human lymphoblastoid TK6 cells.

The use of manual microscopy for the scoring of chromosome damage in the in vitro micronucleus assay is often associated with user subjectivity. This level of subjectivity can be reduced by using automated platforms, which have added value of faster with high-throughput and multi-endpoint capabilities. However, there is a need to assess the reproducibility and sensitivity of these automated platforms compared with the gold standard of the manual scoring. The automated flow cytometry-based MicroFlow® and image analysis-based Metafer™ were used for dose response analyses in human lymphoblastoid TK6 cells exposed to the model clastogen, methyl methanesulfonate (MMS), aneugen, carbendazim, and the weak genotoxic carcinogen, ochratoxin A (OTA). Cells were treated for 4 or 30 h, with a 26- or 0-h recovery. Flow cytometry scoring parameters and the Metafer™ image classifier were investigated, to assess any potential differences in the micronucleus (MN) dose responses. Dose response data were assessed using the benchmark dose approach with chemical and scoring system set as covariate to assess reproducibility between endpoints. A clear increase in MN frequency was observed using the MicroFlow® approach on TK6 cells treated for 30 h with MMS, carbendazim and OTA. The MicroFlow®-based MN frequencies were comparable to those derived by using the Metafer™ and manual scoring platforms. However, there was a potential overscoring of MN with the MicroFlow® due to the cell lysis step and an underscoring with the Metafer™ system based on current image classifier settings. The findings clearly demonstrate that the MicroFlow® and Metafer™ MN scoring platforms are powerful tools for automated high-throughput MN scoring and dose response analysis.

Genetic toxicology at the crossroads-from qualitative hazard evaluation to quantitative risk assessment.

Applied genetic toxicology is undergoing a transition from qualitative hazard identification to quantitative dose-response analysis and risk assessment. To facilitate this change, the Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC) sponsored a workshop held in Lancaster, UK on July 10-11, 2014. The event included invited speakers from several institutions and the contents was divided into three themes-1: Point-of-departure Metrics for Quantitative Dose-Response Analysis in Genetic Toxicology; 2: Measurement and Estimation of Exposures for Better Extrapolation to Humans and 3: The Use of Quantitative Approaches in Genetic Toxicology for human health risk assessment (HHRA). A host of pertinent issues were discussed relating to the use of in vitro and in vivo dose-response data, the development of methods for in vitro to in vivo extrapolation and approaches to use in vivo dose-response data to determine human exposure limits for regulatory evaluations and decision-making. This Special Issue, which was inspired by the workshop, contains a series of papers that collectively address topics related to the aforementioned themes. The Issue includes contributions that collectively evaluate, describe and discuss in silico, in vitro, in vivo and statistical approaches that are facilitating the shift from qualitative hazard evaluation to quantitative risk assessment. The use and application of the benchmark dose approach was a central theme in many of the workshop presentations and discussions, and the Special Issue includes several contributions that outline novel applications for the analysis and interpretation of genetic toxicity data. Although the contents of the Special Issue constitutes an important step towards the adoption of quantitative methods for regulatory assessment of genetic toxicity, formal acceptance of quantitative methods for HHRA and regulatory decision-making will require consensus regarding the relationships between genetic damage and disease, and the concomitant ability to use genetic toxicity results per se.

Estimating the carcinogenic potency of chemicals from the in vivo micronucleus test.

In this study, we investigated the applicability of using in vivo mouse micronucleus (MN) data to derive cancer potency information. We also present a new statistical methodology for correlating estimated potencies between in vivo MN tests and cancer studies, which could similarly be used for other systems (e.g. in vitro vs. in vivo genotoxicity tests). The dose-response modelling program PROAST was used to calculate benchmark doses (BMDs) for estimating the genotoxic and carcinogenic potency for 48 compounds in mice; most of the data were retrieved from the National Toxicology Program (NTP) database, while some additional data were retrieved from the Carcinogenic Potency Database and published studies. BMD05s (doses with 5% increase in MN frequency) were derived from MN data, and BMD10s (doses with 10% extra cancer risk) were derived from carcinogenicity data, along with their respective lower (BMDL) and upper (BMDU) confidence bounds. A clear correlation between the in vivo MN BMD05s and the cancer BMD10s was observed when the lowest BMD05 from the in vivo MN was plotted against the lowest BMD10 from the carcinogenicity data for each individual compound. By making a further selection of BMDs related to more or less equally severe cancer lesions, the correlation was considerably improved. Getting a general scientific consensus on how we can quantitatively compare different tumour lesion types and investigating the impact of MN study duration are needed to refine this correlation analysis. Nevertheless, our results suggest that a BMD derived from genotoxicity data might provide a prediction of the tumour potency (BMD10) with an uncertainty range spanning roughly a factor of 100.

Genotoxicity of flubendazole and its metabolites in vitro and the impact of a new formulation on in vivo aneugenicity.

The anti-parasitic benzimidazole flubendazole has been used for many years to treat intestinal infections in humans and animals. Previous genotoxicity studies have shown that the compound is not a bacterial mutagen and a bone marrow micronucleus test, using a formulation that limited systemic absorption, was negative. The purpose of this study is to explore the genotoxicity of flubendazole and its main metabolites in in vitro micronucleus studies and to test a new oral formulation that improves systemic absorption in an in vivo micronucleus test. The isolated metabolites were also screened using the Ames test for bacterial mutagenicity. It was found that flubendazole, like other chemically related benzimidazoles used in anti-parasitic therapies, is a potent aneugen in vitro The hydrolysed metabolite of flubendazole is negative in these tests, but the reduced metabolite (R- and S-forms) shows both aneugenic and clastogenic activity. However, in vitro micronucleus tests of flubendazole in the presence of rat liver S9 gave almost identical signals for aneugenicity as they did in the absence of S9, suggesting that any clastogenicity from the reduced metabolite is not sufficient to change the overall profile. Like flubendazole itself, both metabolites are negative in the Ames test. Analysis of dose-response curves from the in vitro tests, using recently developed point of departure approaches, demonstrate that the aneugenic potency of flubendazole is very similar to related anti-parasitic benzimidazoles, including albendazole, which is used in mass drug administration programmes to combat endemic filarial diseases. The in vivo micronucleus test of the new formulation of flubendazole also showed evidence of induced aneugenicity. Analysis of the in vivo data allowed a reference dose for aneugenicity to be established which can be compared with therapeutic exposures of flubendazole when this has been established. Analysis of the plasma from the animals used in the in vivo micronucleus test showed that there is increased exposure to flubendazole compared with previously tested formulations, as well as significant formation of the non-genotoxic hydrolysed metabolite of flubendazole and small levels of the reduced metabolite. In conclusion, this study shows that flubendazole is a potent aneugen in vitro with similar potency to chemically related benzimidazoles currently used as anti-parasitic therapies. The reduced metabolite also has aneugenic properties as well as clastogenic properties. Treatment with a new formulation of flubendazole that allows increased systemic exposure, compared with previously used formulations, also results in detectable aneugenicity in vivo. Based on the lack of carcinogenicity of this class of benzimidazoles and the intended short-term dosing, it is unlikely that flubendazole treatment will pose a carcinogenic risk to patients.

Empirical analysis of BMD metrics in genetic toxicology part I: in vitro analyses to provide robust potency rankings and support MOA determinations.

Genetic toxicity testing has traditionally been used for hazard identification, with dichotomous classification of test results serving to identify genotoxic agents. However, the utility of genotoxicity data can be augmented by employing dose-response analysis and point of departure determination. Via interpolation from a fitted dose-response model, the benchmark dose (BMD) approach estimates the dose that elicits a specified (small) effect size. BMD metrics and their confidence intervals can be used for compound potency ranking within an endpoint, as well as potency comparisons across other factors such as cell line or exposure duration. A recently developed computational method, the BMD covariate approach, permits combined analysis of multiple dose-response data sets that are differentiated by covariates such as compound, cell type or exposure regime. The approach provides increased BMD precision for effective potency rankings across compounds and other covariates that pertain to a hypothesised mode of action (MOA). To illustrate these applications, the covariate approach was applied to the analysis of published in vitro micronucleus frequency dose-response data for ionising radiations, a set of aneugens, two mutagenic azo compounds and a topoisomerase II inhibitor. The ionising radiation results show that the precision of BMD estimates can be improved by employing the covariate method. The aneugen analysis provided potency groupings based on the BMD confidence intervals, and analyses of azo compound data from cells lines with differing metabolic capacity confirmed the influence of endogenous metabolism on genotoxic potency. This work, which is the first of a two-part series, shows that BMD-derived potency rankings can be employed to support MOA evaluations as well as facilitate read across to expedite chemical evaluations and regulatory decision-making. The follow-up (Part II) employs the combined covariate approach to analyse in vivo genetic toxicity dose-response data focussing on how improvements in BMD precision can impact the reduction and refinement of animal use in toxicological research.

MutAIT: an online genetic toxicology data portal and analysis tools.

Assessment of genetic toxicity and/or carcinogenic activity is an essential element of chemical screening programs employed to protect human health. Dose-response and gene mutation data are frequently analysed by industry, academia and governmental agencies for regulatory evaluations and decision making. Over the years, a number of efforts at different institutions have led to the creation and curation of databases to house genetic toxicology data, largely, with the aim of providing public access to facilitate research and regulatory assessments. This article provides a brief introduction to a new genetic toxicology portal called Mutation Analysis Informatics Tools (MutAIT) (www.mutait.org) that provides easy access to two of the largest genetic toxicology databases, the Mammalian Gene Mutation Database (MGMD) and TransgenicDB. TransgenicDB is a comprehensive collection of transgenic rodent mutation data initially compiled and collated by Health Canada. The updated MGMD contains approximately 50 000 individual mutation spectral records from the published literature. The portal not only gives access to an enormous quantity of genetic toxicology data, but also provides statistical tools for dose-response analysis and calculation of benchmark dose. Two important R packages for dose-response analysis are provided as web-distributed applications with user-friendly graphical interfaces. The 'drsmooth' package performs dose-response shape analysis and determines various points of departure (PoD) metrics and the 'PROAST' package provides algorithms for dose-response modelling. The MutAIT statistical tools, which are currently being enhanced, provide users with an efficient and comprehensive platform to conduct quantitative dose-response analyses and determine PoD values that can then be used to calculate human exposure limits or margins of exposure.

Empirical analysis of BMD metrics in genetic toxicology part II: in vivo potency comparisons to promote reductions in the use of experimental animals for genetic toxicity assessment.

Genotoxicity tests have traditionally been used only for hazard identification, with qualitative dichotomous groupings being used to identify compounds that have the capacity to induce mutations and/or cytogenetic alterations. However, there is an increasing interest in employing quantitative analysis of in vivo dose-response data to derive point of departure (PoD) metrics that can be used to establish human exposure limits or margins of exposure (MOEs), thereby supporting human health risk assessments and regulatory decisions. This work is an extension of our companion article on in vitro dose-response analyses and outlines how the combined benchmark dose (BMD) approach across included covariates can be used to improve the analyses and interpretation of in vivo genetic toxicity dose-response data. Using the BMD-covariate approach, we show that empirical comparisons of micronucleus frequency dose-response data across multiple studies justifies dataset merging, with subsequent analyses improving the precision of BMD estimates and permitting attendant potency ranking of seven clastogens. Similarly, empirical comparisons of Pig-a mutant phenotype frequency data collected in males and females justified dataset merging across sex. This permitted more effective scrutiny regarding the effect of post-exposure sampling time on the mutagenicity of N-ethyl-N-nitrosourea observed in reticulocytes and erythrocytes in the Pig-a assay. The BMD-covariate approach revealed tissue-specific differences in the induction of lacZ transgene mutations in Muta™Mouse specimens exposed to benzo[a]pyrene (BaP), with the results permitting the formulation of mechanistic hypotheses regarding the observed potency ranking. Lastly, we illustrate how historical dose-response data for assessments that examined numerous doses (i.e. induced lacZ mutant frequency (MF) across 10 doses of BaP) can be used to improve the precision of BMDs derived from datasets with far fewer doses (i.e. lacZ MF for 3 doses of dibenz[a,h]anthracene). Collectively, the presented examples illustrate how innovative use of the BMD approach can permit refinement of the use of in vivo data; improving the efficacy of experimental animal use in genetic toxicology without sacrificing PoD precision.